Wei Tianjun, Wei Wei, Ma Qiang, Shen Zhongbing, Lu Kebing, Zhu Xiangming
School of Continuing Education, Anhui Medical University, Hefei, 230032, People's Republic of China.
Department of Ultrasound, The First Affiliated Hospital of Wannan Medical College, Wuhu, 241001, People's Republic of China.
Int J Gen Med. 2023 Aug 29;16:3921-3932. doi: 10.2147/IJGM.S424880. eCollection 2023.
Papillary thyroid carcinoma (PTC) is a prevalent histological type of thyroid cancer; however, noninvasive assessment of cervical lymph node metastasis (LNM) poses a challenge. This study aims to develop a novel clinical-radiomics nomogram that utilizes ultrasound (US) images to predict the presence of cervical LNM metastasis in patients with PTC.
A total of 423 patients with PTC were recruited to participate in this study between January 2020 and December 2022, of which 282 were classified into the training group and 141 patients were classified into the validation set. Contrast-enhanced ultrasound (CEUS) and B-mode ultrasound (BMUS) images were subjected to radiomic analysis, leading to the extraction of 912 radiomic features. Thereafter, a radiomics score (Radscore) was developed to effectively integrate the information derived from BMUS and CEUS modalities. Univariate and multivariate backward stepwise logistic regression analysis techniques were used to construct the clinical and clinical-radiomics models, respectively.
The findings revealed that the clinical-radiomics nomogram incorporated age, sex, CEUS Radscore, and US-reported LNM as risk factors. The nomogram demonstrated good performance using data from the training (AUC = 0.891) and validation (AUC = 0.870) sets. The decision curve analysis implied that this nomogram exhibited good clinical utility, which was further supported by the results of the calibration curves and Hosmer-Lemeshow test.
The CEUS Radscore-based clinical radiomics nomogram could serve as a valuable tool for predicting cervical LNM metastasis in patients with PTC, thereby tailoring individualized treatment strategies for them.
甲状腺乳头状癌(PTC)是一种常见的甲状腺癌组织学类型;然而,对颈部淋巴结转移(LNM)进行无创评估具有挑战性。本研究旨在开发一种新型的临床-影像组学列线图,利用超声(US)图像预测PTC患者颈部LNM转移的存在。
2020年1月至2022年12月期间,共招募了423例PTC患者参与本研究,其中282例被分为训练组,141例患者被分为验证集。对超声造影(CEUS)和B型超声(BMUS)图像进行影像组学分析,提取912个影像组学特征。此后,开发了一个影像组学评分(Radscore),以有效整合来自BMUS和CEUS模式的信息。分别采用单因素和多因素向后逐步逻辑回归分析技术构建临床和临床-影像组学模型。
研究结果显示,临床-影像组学列线图纳入年龄、性别、CEUS Radscore和超声报告的LNM作为危险因素。使用来自训练集(AUC = 0.891)和验证集(AUC = 0.870)的数据,该列线图表现出良好的性能。决策曲线分析表明,该列线图具有良好的临床实用性,校准曲线和Hosmer-Lemeshow检验的结果进一步支持了这一点。
基于CEUS Radscore的临床影像组学列线图可作为预测PTC患者颈部LNM转移的有价值工具,从而为他们制定个性化的治疗策略。